Techpowerup has published a redacted presentation from an unnamed AI company to an unnamed big-budget multiplayer video-game publisher, setting out a suite of surveillance capitalism tools combined with machine-learning to manipulate players to make them as addicted as possible and drain them of as much money as possible.
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Reddit has shut down /r/deepfakes, the subreddit where people collaborate to produce incredibly disturbing faceswapped pornography that uses machine-learning to put the faces of famous people who aren't pornography performers onto the bodies of people having sex in pornographic videos.
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Late last year, a redditor called Deepfakes gained notoriety for the extremely convincing face-swap porn videos he was making, in which the faces of mainstream Hollywood actors and rockstars were convincingly overlaid on the bodies of performers in pornography.
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A new report from the New America Foundation uses the current fear that Russian government elements manipulated the 2016 US election to explore the relationship between advertising technology, surveillance capitalism, and "precision propaganda," showing how the toolsuite developed for the advertising industry is readily repurposable by even modestly competent actors to spread disinformation campaigns.
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Google's Cloud Automl Vision system -- a machine-learning-based image classifier -- is now available to the general public; anyone can sign up to the program, upload a set of 20-10,000 images and train a new model with them, which they can then use.
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Machine learning systems trained for object recognition deploy a bunch of evolved shortcuts to choose which parts of an image are important to their classifiers and which ones can be safely ignored.
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YouTuber CGP Grey is known for breaking down complex subjects so that they can be understood by just about anyone. His most recent animated video is no exception. In it, he answers the question, "How do all the algorithms around us learn to do their jobs?," ie. how do machines learn? Good stuff.

Why do billionaires like Elon Musk make terrified pronouncements about the imminent rise of self-aware, murderous AIs that use us to reproduce themselves, controlling us instead of serving us?
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"The Trouble with Bias," Kate Crawford's (previously) keynote at the 2017 Neural Information Processing Systems is a brilliant tour through different ways of thinking about what bias is, and when we should worry about it, specifically in the context of machine learning systems and algorithmic decision making -- the best part is at the end, where she describes what we should do about this stuff, and where to get started. (via 4 Short Links)
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In a pair of open letters to Letter to The Honorable Elaine C. Duke, Acting Secretary of Homeland, a coalition of more than 100 tech liberties groups and leading technology experts urged the DHS to abandon its plan to develop a black-box algorithmic system for predicting whether foreigners coming to the USA to visit or live are likely to be positive contributors or risks to the nation.
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A group of NYU and University of Illinois at Chicago computer scientists have presented a paper at the 2017 ACM Internet Measurement Conference in London presenting their findings in a large-scale study of online doxings, with statistics on who gets doxed (the largest cohort being Americann, male, gamers, and in their early 20s), why they get doxed ("revenge" and "justice") and whether software can detect doxing automatically, so that human moderators can take down doxing posts quickly.
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The Vietnamese security company Bkav says that a prototype mask costing $150 can reliably defeat Apple's Face ID authentication system. However, the company (which has a good track record for defeating facial recognition systems) has not released technical details for the defeat and says that it was able to accomplish the task "Because... we are the leading cyber security firm ;)."
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There are 50 hospitals on 5 continents that use Watson for Oncology, an IBM product that charges doctors to ingest their cancer patients' records and then make treatment recommendations and suggest journal articles for further reading.
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